Predictive modeling of adverse drug reactions to tamoxifen therapy for breast cancer on base of pharmacogenomic testing

Abstract

Objectives The present study investigated the analysis of adverse drug reactions (ADRs) to Tamoxifen (TAM) in breast cancer patients in relation to the carriage of genetic polymorphisms of genes encoding enzymes of CYP system and transporters of P-glycoprotein (Pg) and predictive models based on it. Methods 120 women with breast cancer taking adjuvant TAM were examined for the gene polymorphisms such as CYP2D6*4, CYP3A5*3, CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2C19*3 and ABCB1 (C3435T). Allelic variants were determined using the real-time polymerase chain reaction method. The research material was double sampling of buccal epithelium. Medical history data and extracts from case histories were used as sources of medical information, on the basis of which questionnaires specially created by us were filled out. Results An associative analysis showed association with the development of ADRs to tamoxifen indicating their clinical significance from different genetic polymorphisms of CYP2D6, CYP3A5, CYP2C9 and ABCB1. The complex associative analysis performed using mathematical modeling made it possible to build predictive risk models for the development of ADRs such as hot flashes, dyspepsia, bone pain, and asthenia. Conclusions Models that include both genetic and non-genetic determinants of ADRs of TAM may further improve the prediction of individual response to tamoxifen.